Predicting Renal Function Outcomes After Partial and Radical Nephrectomy.

Area of Science:

• Nephrology
• Urology
• Oncology

Background:

• Partial nephrectomy (PN) is preferred for cT1 tumors over radical nephrectomy (RN) when feasible.
• The renal function benefit of PN versus RN can be uncertain.
• Predicting long-term outcomes is crucial for surgical decision-making.

Purpose of the Study:

• Develop preoperative tools to predict estimated glomerular filtration rate (eGFR) beyond 30 days after PN and RN.
• Provide data to aid in the risk-benefit analysis of PN versus RN.
• Enhance patient counseling regarding kidney function after surgery.

Main Methods:

• Retrospective cohort study of patients undergoing RN or PN for renal tumors (1997-2014).
• Hierarchical generalized linear mixed-effect models used to predict long-term eGFR.
• Models selected preoperative features using backward selection.

Main Results:

• Models were developed for both RN (marginal R_GLMM²=0.41) and PN.
• RN model included: age, diabetes, preoperative eGFR, proteinuria, tumor size, time from surgery, and age-time interaction.
• PN model included: age, solitary kidney, diabetes, hypertension, preoperative eGFR, proteinuria, surgical approach, time from surgery, and multiple interaction terms.

Conclusions:

• Preoperative tools were developed to predict renal function after RN and PN.
• These tools can assist in patient counseling and clinical decision-making.
• External validation is needed to confirm generalizability.